Inter-array Data Regrouping

2000 ◽  
pp. 149-163 ◽  
Author(s):  
Chen Ding ◽  
Ken Kennedy
Keyword(s):  
Array Data

The Farallones moored array data report

1993 ◽  
Author(s):  
K.L. Kinoshita ◽  
M.A. Noble ◽  
S.R. Ramp
Keyword(s):  
Array Data

Reconstruction of Protein Networks Using Reverse-Phase Protein Array Data

2016 ◽  
pp. 227-246
Author(s):  
Silvia von der Heyde ◽  
Johanna Sonntag ◽  
Frank Kramer ◽  
Christian Bender ◽  
Ulrike Korf ◽  
...  
Keyword(s):  
Protein Array ◽  
Protein Networks ◽  
Reverse Phase Protein Array ◽  
Reverse Phase ◽  
Array Data ◽  
Phase Protein

Toward blind joint demosaicing and denoising of raw color filter array data

2021 ◽  
Author(s):  
Fangfang Wu ◽  
Tao Huang ◽  
Weisheng Dong ◽  
Guangming Shi ◽  
Zhonglong Zheng ◽  
...  
Keyword(s):  
Color Filter ◽  
Color Filter Array ◽  
Array Data ◽  
Filter Array

scholarly journals Comparison of spatial processing techniques for sonar array data

1988 ◽  
Vol 84 (S1) ◽  
pp. S16-S16
Author(s):  
David V. Wyllie ◽  
Brian G. Ferguson ◽  
Garry C. Speechley
Keyword(s):  
Spatial Processing ◽  
Array Data ◽  
Processing Techniques

scholarly journals EWAS Data Hub: a resource of DNA methylation array data and metadata

2019 ◽  
Vol 48 (D1) ◽  
pp. D890-D895 ◽  
Author(s):  
Zhuang Xiong ◽  
Mengwei Li ◽  
Fei Yang ◽  
Yingke Ma ◽  
Jian Sang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Complex Traits ◽  
Cell Types ◽  
Great Promise ◽  
Methylation Array ◽  
Array Data ◽  
The Past ◽  
Comprehensive Collection ◽  
Dna Methylation Array ◽  
Brain Parts

Abstract Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

Solving for Source Parameters Using Nested Array Data: A Case Study from the Canterbury, New Zealand Earthquake Sequence

2016 ◽  
Vol 174 (3) ◽  
pp. 875-893 ◽  
Author(s):  
Corrie Neighbors ◽  
E. S. Cochran ◽  
K. J. Ryan ◽  
A. E. Kaiser
Keyword(s):  
New Zealand ◽  
Source Parameters ◽  
Earthquake Sequence ◽  
Array Data
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